Younger Adults Derive Pleasure and Utilitarian Benefits from Browsing for Music Information Seeking in Physical and Digital Spaces. A Review of: Laplante, A., & Downie, J. S. (2011). The utilitarian and hedonic outcomes of music information-seeking in everyday life. Library & Information Science Research, 33, 202-210. doi:10.1016/j.lisr.2010.11.002
Notice bibliographique
Résumé
<b>Objective</b> – This study’s objective was to identify the utilitarian and hedonic features of satisfying music information seeking experiences from the perspective of younger adults when using physical and digital music information retrieval (MIR) systems in their daily lives.<br><b>Design</b> – In-depth, semi-structured interviews.<br><b>Setting</b> – Large public library in Montreal, Canada.<br><b>Subjects</b> – 15 French-speaking younger adults,10 males and 5 females (aged 18 to 29 years, mean age of 24 years).<br><b>Methods</b> – A pre-test was completed to test the interview guide. The guide was dividedinto five sections asking the participants questions about their music tastes, how music fit into their daily lives, how they discovered music, what music information sources were used and how they were used, what made their experiences satisfying, and theirbiographical information. Participants were recruited between April 1, 2006 and August 8,2007 following maximum variation samplingfor the main study. Recruitment stopped whendata saturation was reached and no new themes arose during analysis. Interviews were recorded and the transcripts were analyzed via constant comparative method (CCM) to determine themes and patterns. <br><b>Main Results</b> – The researchers found that both utilitarian and hedonic factors contributed to satisfaction with music information seeking experiences for the young adults. Utilitarian factors were divided between two main categories: finding music and finding information about music. Finding information about music could be further divided into three sub-categories: increasing cultural knowledge and social acceptance through increased knowledge about music, enriching the listening experience by finding information about the artist and the music, and gathering information to help with future music purchases including information that would help the participants recommend music to others. Hedonic outcomes that contributed to satisfying information seeking experiences included deriving pleasure and feeling engaged while searching or browsing for music. Especially satisfying experiences were those where the participants felt highly engaged in the process and found new, independent, non-mainstream music. Not finding new music did not automatically lead to an unsatisfying experience for the participants; however, technology malfunctions in digital MIR systems and unpleasant environments such as those with unfriendly staff in physical music spaces (libraries and stores), led to unsatisfying experiences for the participants.<br><b>Conclusions</b> – As the results show that the hedonic aspects of music information seeking are very important, designers of MIR systems must take into account the hedonic as well as utilitarian outcomes when creating user interfaces. MIR systems should be designed with browsing as well as searching capabilities so searchers can make serendipitous discoveries of new music and information about music. In other words, MIR systems need to be engaging to ensure satisfying interactions for searchers.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,002 | 0,089 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».